/**
 * @verevoir/llm/google — Google Gemini SDK adapter.
 *
 * Wraps `@google/genai` in the provider-agnostic surface defined in the
 * core. Importing this subpath requires `@google/genai` as a peer
 * dependency on the consumer.
 *
 * v0.4.0 ships `chat()` only — single-shot text generation. The
 * materialiser-style paths (review-repo, doc-piece, conversation-doc)
 * use just this. `chatWithTools()` and `chatWithToolLoop()` follow in
 * a subsequent release.
 */
import { type ChatOptions, type ChatReply, type ChatWithToolLoopOptions, type ChatWithToolLoopResult, type ChatWithToolsOptions, type ChatWithToolsResult, type ModelClass, type RatesTable } from '../index.js';
/** Provider id reported on every {@link TokenUsage} this adapter returns. */
export declare const PROVIDER = "google";
/**
 * Concrete model id per {@link ModelClass}. Reasoning maps to the
 * most-capable Pro tier; extraction maps to Flash, which Google
 * positions for fast/cheap structured tasks.
 *
 * As of 2026-05-20 we use 2.5-family identifiers (current general
 * availability); upgrades happen here only, no ripple through callers.
 */
export declare const models: Readonly<Record<ModelClass, string>>;
/**
 * Per-model pricing (USD per million tokens) — Google-published rates
 * as of 2026-05-20.
 *
 * **Worst-case approach:** same convention as the Anthropic adapter —
 * cached input is billed cheaper than standard but the rate-tuple
 * here is the standard input rate, so pricing via this table is an
 * upper bound. Refresh this table when Google publishes new
 * pricing.
 *
 * Each rate-tuple is `[input_per_million_USD, output_per_million_USD]`.
 *
 * @deprecated Part of the old static-rates cost API. Use
 * `createPriceBook(...)` / `book.costOf(...)` instead (see `src/pricing.ts`)
 * — it prices from LiteLLM's live table (the bundled snapshot as fallback)
 * and reports an unmatched model as `unpriced` rather than `0`.
 */
export declare const rates: RatesTable;
/**
 * Single-shot text generation via the Gemini API. Same surface as the
 * Anthropic adapter's `chat()`: pass turns + systemPrompt, get
 * `{ content, usage, stopReason }` back. Retry on transient errors
 * with caller-visible narration via `onRetry`.
 *
 * Not yet supported in this adapter (planned follow-up): live progress
 * narration via `onProgress` (Gemini's streaming + tool semantics need
 * a different shape from Anthropic's report_progress pattern).
 */
export declare function chat(options: ChatOptions): Promise<ChatReply>;
/** Single-shot tool-calling: surface the model's functionCalls for the caller
 * to execute. Mirrors the Anthropic adapter's chatWithTools. */
export declare function chatWithTools(options: ChatWithToolsOptions): Promise<ChatWithToolsResult>;
/** Multi-turn tool loop: model → execute tools → feed functionResponse parts
 * back, until the model returns a call-free reply (or maxIterations). Mirrors
 * the Anthropic adapter's chatWithToolLoop, in Gemini's content shape. */
export declare function chatWithToolLoop(options: ChatWithToolLoopOptions): Promise<ChatWithToolLoopResult>;
//# sourceMappingURL=index.d.ts.map